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@sunmeat
sunmeat / Program.cs
Created September 23, 2026 12:36
Firebase Authentication + перевірка на боці бекенду
using Microsoft.AspNetCore.Authentication.JwtBearer;
using Microsoft.IdentityModel.Tokens; // ця бібліотека потрібна для валідації JWT токенів
using Soccer.Application.DependencyInjection;
using Soccer.Infrastructure.DependencyInjection;
using Soccer.Infrastructure.Persistence;
// View > Terminal:
// cd Soccer.WebAPI
// dotnet add package Microsoft.AspNetCore.Authentication.JwtBearer
// ця бібліотека потрібна для аутентифікації через JWT токени, які видає Firebase
@bradtraversy
bradtraversy / terminal-commands.md
Last active September 23, 2026 12:32
Common Terminal Commands

Common Terminal Commands

Key Commands & Navigation

Before we look at some common commands, I just want to note a few keyboard commands that are very helpful:

  • Up Arrow: Will show your last command
  • Down Arrow: Will show your next command
  • Tab: Will auto-complete your command
  • Ctrl + L: Will clear the screen

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@MohamedAlaa
MohamedAlaa / tmux-cheatsheet.markdown
Last active September 23, 2026 12:28
tmux shortcuts & cheatsheet

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname
@drillan
drillan / jev-finance-projects.md
Created September 20, 2026 02:27
Jev (TypeSafe System One) finance & trading projects — surveyed 2026-09-20

Jev (TypeSafe System One) — Finance & Trading Projects

Projects using Jev, TypeSafe AI's System One decision model (released 2026-09-15), in investment, trading, and financial-data contexts. Surveyed 2026-09-20 via GitHub API and community awesome-lists.

Reference project

  • jarrodwatts/jev-trader (★1.3k, 2026-09-16) — One AI trade decision every Monad block (~300 ms). Jev reads the Kuru MON-USDC order book and answers buy or sell; the bot posts a post-only limit order one tick inside the touch, earning the spread. Bun/TypeScript, dry-run mode, SSE dashboard. The template most projects below derive from.

Live trading / trading systems

@fin77n-ai
fin77n-ai / README.md
Last active September 23, 2026 12:24
Curated Apple TV global news M3U playlist with data-use estimates

Apple TV Curated Free Channels

Curated on 2026-08-02 for APTV. The collection contains publicly accessible news, documentary, and free sports streams verified from Japan at publication time.

One-link playlist

Import atv-curated.m3u to get all 25 channels in three ordered groups:

  • 01 全球新闻: 10 channels.
  • 02 纪录片: 7 channels.
@dabit3
dabit3 / pi_tutorial.md
Last active September 23, 2026 12:24
How to Build a Custom Agent Framework with PI: The Agent Stack Powering OpenClaw

PI is a TypeScript toolkit for building AI agents. It's a monorepo of packages that layer on top of each other: pi-ai handles LLM communication across providers, pi-agent-core adds the agent loop with tool calling, pi-coding-agent gives you a full coding agent with built-in tools, session persistence, and extensibility, and pi-tui provides a terminal UI for building CLI interfaces.

These are the same packages that power OpenClaw. This guide walks through each layer, progressively building up to a fully featured coding assistant with a terminal UI, session persistence, and custom tools.

By understanding how to compose these layers, you can build production-grade agentic software on your own terms, without being locked into a specific abstraction.

Pi was created by @badlogicgames. This is a great writeup from him that explains some of the design decisions made when creating it.

The stack

@8ctopotamus
8ctopotamus / Fetch.cs
Created August 27, 2019 17:40
Fetch data from REST API in C# example
using System.IO;
using System.Net;
namespace ConsoleApp1
{
class Program
{
static void Main(string[] args)
{
System.Net.ServicePointManager.SecurityProtocol = SecurityProtocolType.Tls12;